Resolution and uniqueness of estimated parameters of a model of thin filament regulation in solution

Computational Biology and Chemistry

Volumn 34, Issue 1, 2010, Pages 19-33

  Mijailovich, Srboljub M ^a   Li, Xiaochuan ^a   del Álamo, Juan C ^a,b   Griffiths, R Hugh ^c   Kecman, Vojislav ^d   Geeves, Michael A ^c  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF KENT   (United Kingdom)

^d Virginia Commonwealth University   (United States)

Author keywords

Ca2+ sensitivity; Damped Least Squares; Resolution matrix; Stopped flow; Tropomyosin troponin actin

Indexed keywords

DAMPED LEAST SQUARES; RESOLUTION MATRIX; STOPPED FLOW; TROPOMYOSIN; TROPONIN;

CALCIUM; DYNAMIC LIGHT SCATTERING; DYNAMIC LOADS; FILAMENTS (LAMP); FLUORESCENCE; GLOBAL OPTIMIZATION; GRAFTING (CHEMICAL); LAWS AND LEGISLATION; NONLINEAR EQUATIONS; ORDINARY DIFFERENTIAL EQUATIONS; PARAMETER ESTIMATION; PROTEINS; SIMULATED ANNEALING; SYNTHESIS (CHEMICAL); TRANSIENTS;

RATE CONSTANTS;

ACTIN; MYOSIN; TROPOMYOSIN; TROPONIN;

ALGORITHM; ARTICLE; CHEMICAL MODEL; CHEMISTRY; COMPUTER SIMULATION; KINETICS; METABOLISM; MICROFILAMENT; REGRESSION ANALYSIS; SOLUTION AND SOLUBILITY;

ACTINS; ALGORITHMS; COMPUTER SIMULATION; KINETICS; LEAST-SQUARES ANALYSIS; MICROFILAMENTS; MODELS, CHEMICAL; MYOSINS; SOLUTIONS; TROPOMYOSIN; TROPONIN;

EID: 75149132048     PISSN: 14769271     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiolchem.2009.11.002     Document Type: Article

References (33)

1. Arora N., and Biegler L.T. A trust region SQP algorithm for equality constrained parameter estimation with simple parameter bounds. Comput. Optim. Appl. 28 (2004) 51
2. Beck J.V., and Arnold K.J. In: Bradley R.A., Kendall D.G., Hunter J.S., and Watson G.S. (Eds). Parameter Estimation in Engineering and Science (1977), John Wiley & Sons, New York
3. Boussouf S.E., Agianian B., Bullard B., and Geeves M.A. The regulation of myosin binding to actin filaments by Lethocerus troponin. J. Mol. Biol. 373 3 (2007) 587-598
4. Boussouf S.E., and Geeves M.A. Tropomyosin and troponin cooperativity on the thin filament. Adv. Exp. Med. Biol. 592 (2007) 99-109
5. Boussouf S.E., Maytum R., Jaquet K., and Geeves M.A. Role of tropomyosin isoforms in the calcium sensitivity of striated muscle thin filaments. J. Muscle Res. Cell Motil. 28 (2007) 49-58
6. Chen Y., Yan B., Chalovich J.M., and Brenner B. Theoretical kinetic studies of models for binding myosin subfragment-1 to regulated actin: Hill model versus Geeves model. Biophys. J. 80 5 (2001) 2338-2349
7. Dennis Jr. J.E., and Schnabel R.B. Numerical Methods for Unconstrained Optimization and Nonlinear Equations (1983), Prentice-Hall, Englewood Cliffs, NJ
8. Dennis Jr. J.E., and Schnabel R.B. A view of unconstrained optimization. In: Nemhauser G.L., Runnooy Kan A.H.G., and Todd M.J. (Eds). Handbook in Operations Research and Management Science (1989), Elsevier, Amsterdam
9. Eftaxias A., Font J., Fortuny A., Fabregat A., and Stuber F. Nonlinear kinetic parameter estimation using simulated annealing. Comput. Chem. Eng. 26 12 (2002) 1725-1733
10. Farinha J.P.S., Martinho J.M.G., and Pogliani L. Non-linear least-squares and chemical kinetics. An improved method to analyse monomer-excimer decay data. J. Math. Chem. 21 (1997) 131-139
11. Frank P.M. Introduction to System Sensitivity Theory (1978), Academic, New York
12. Gill, P.E., Murray, W., 1976. Minimization Subject to Bounds on the Variables. NPL Report NAC 72, National Physical Laboratory, Teddington, UK.
13. Goffe W., Ferrier G.D., and Rogers J. Global optimization of statistical functions with simulated annealing. J. Econ. 60 (1994) 65-99
14. Hill T.L., Eisenberg E., and Greene L. Theoretical model for the cooperative equilibrium binding of myosin subfragment 1 to the actin-troponin-tropomyosin complex. Proc. Natl. Acad. Sci. U.S.A. 77 6 (1980) 3186-3190
15. Hindmarsh A.C. GEAR: Ordinary Differential Equation System Solver (1972)
16. Kecman V. Learning and Soft Computing (2001), The MIT Press, Cambridge, MA
17. Kirkpatrick S., Gelatt Jr. C.D., and Vecchi M.P. Optimization by simulated annealing. Science 220 4598 (1983) 671-680
18. Levenberg K. A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 2 (1944) 164-168
19. Lisy J.M., and Simon P. Evaluation of parameters in nonlinear models by the least squares method. Comput. Chem. 22 6 (1998) 509-513
20. Maytum R., Lehrer S.S., and Geeves M.A. Cooperativity and switching within the three-state model of muscle regulation. Biochemistry 38 3 (1999) 1102-1110
21. McKillop D.F., and Geeves M.A. Regulation of the interaction between actin and myosin subfragment 1: evidence for three states of the thin filament. Biophys. J. 65 2 (1993) 693-701
22. Menke W. In: Dmowska R., and Holton J.R. (Eds). Geophysical Data Analysis: Discrete Inverse Theory (1989), Academic Press, Inc., San Diego, CA
23. Nocedal J., and Wright S.J. Numerical Optimization (2006), Springer, New York, NY
24. Press W.H., Flannery B.P., Teukolsky S.A., and Vetterling W.T. Numerical Recepies. The Art of Scientific Computing (1986), Cambridge University Press, New York, NY
25. Smith D.A., and Geeves M.A. Cooperative regulation of myosin-actin interactions by a continuous flexible chain II: actin-tropomyosin-troponin and regulation by calcium. Biophys. J. 84 (2003) 3168-3180
26. Smith D.A., Maytum R., and Geeves M.A. Cooperative regulation of myosin-actin interactions by a continuous flexible chain I: actin-tropomyosin systems. Biophys. J. 84 (2003) 3155-3167
27. Tadi M., and Yetter R.A. Evaluation of the rate constants in chemical reactions. Int. J. Chem. Kinet. 30 (1998) 151-159
28. Tang W., Zhang L., Linninger A.A., Tranter R.S., and Brezinsky K. Solving kinetic inversion problems via a physical bounded Gauss-Newton (PGN) method. Ind. Eng. Chem. Res. 44 (2005) 3626-3637
29. Terry D.B., and Messina M. Heuristic search algorithm for determination of rate constants and reaction mechanism from limited concentration data. J. Chem. Inf. Comput. Sci. 38 (1998) 1232
30. Tomovic R., and Vukobratovic M. General Sensitivity Theory (1972), Elsevier, New York
31. Vajda S., and Rabitz H. Identifiably and distinguishability of first-order reaction system. J. Phys. Chem. 92 (1988) 701
32. Varma A., Morbidelli M., and Wu H. Parametric Sensitivity in Chemical System (1999), Cambridge University Press, New York
33. Zsely I.G., Zador J., and Turanyi T. How can very different combustion models produce similar results?. Proc. Combust. Inst. 30 (2004) (poster 1F2-11)